Chi-Squared Test:
Used when there is –
Hypothesis predicts a difference/association
An unrelated design (independent groups)
Nominal or ordinal data and comparing frequencies
Step one –
Enter row/column totals (T) into contingency table
Step two –
R×C
Calculate expected values (E) for each cell using T
, where R is rows and C is
columns
Step three –
(O−E)2
Calculate chi-squared ( x ) using grid using observed values (O), use ∑
2
E
Step four –
Calculate degrees of freedom (df), using (no. of rows – 1) x (no. of columns – 1)
Step five–
Find critical value of x 2 using table
Step six–
State the conclusion. If the result is not significant, we accept the null
hypothesis
Used when there is –
Hypothesis predicts a difference/association
An unrelated design (independent groups)
Nominal or ordinal data and comparing frequencies
Step one –
Enter row/column totals (T) into contingency table
Step two –
R×C
Calculate expected values (E) for each cell using T
, where R is rows and C is
columns
Step three –
(O−E)2
Calculate chi-squared ( x ) using grid using observed values (O), use ∑
2
E
Step four –
Calculate degrees of freedom (df), using (no. of rows – 1) x (no. of columns – 1)
Step five–
Find critical value of x 2 using table
Step six–
State the conclusion. If the result is not significant, we accept the null
hypothesis
